Using step‐selection functions to model landscape connectivity for African elephants: accounting for variability across individuals and seasons

Abstract

Landscape connectivity is an important component of systematic conservation planning.Step-selection functions (SSFs) is a highly promising method for connectivity modeling. However, differences in movement behavior across individuals and seasons are usually not considered in current SSF-based analyses, potentially leading to imprecise connectivity models. Here, our objective was to use SSFs to build functional connectivity models for African elephants Loxodonta africana in a seasonal environment to illustrate the temporal variability of functional landscape connectivity. We provide a methodological framework for integrating detected interindividual variability into resistance surface modeling, for assessing how landscape connectivity changes across seasons, and for evaluating how seasonal connectivity differences affect predictions of movement corridors. Using radio-tracking data from elephants in the Borderland area between Kenya and Tanzania, we applied SSFs to create seasonal landscape resistance surfaces. Based on seasonal models, we predicted movement corridors connecting major protected areas (PAs) using circuit theory and least-cost path analysis. Our findings demonstrate that individual variability and seasonality lead to substantial changes in landscape connectivity and predicted movement corridors. Specifically, we show that the models disregarding seasonal resource fluctuations underestimate connectivity for the wet and transitional seasons, and overestimate connectivity for the dry season. Based on our seasonal models, we predicted a connectivity network between large PAs and highlight seasonal and consistent patterns that are most important for effective management planning. Our findings reveal that elephant movements in the borderland between Kenya and Tanzania are essential for maintaining connectivity in the dry season, and that existing corridors do not protect these movements in full extent.

Towards the restoration of the Mesoamerican Biological Corridor for large mammals in Panama: comparing multi-species occupancy to movement models

“…Since individuals might respond to the environmental covariates differently, it is common practice to use either mixed effects models with individuals as random terms [50], or to average individual coefficients for obtaining coefficients at the population level [51]. However, with high individual-level differences and relatively small sample size, this approach could lead to overgeneralization and spatial biases [52]. Therefore, we developed a SSF for each individual [52] by testing a set of candidate models that included additive uncorrelated covariates as main effects.…”

“…However, with high individual-level differences and relatively small sample size, this approach could lead to overgeneralization and spatial biases [52]. Therefore, we developed a SSF for each individual [52] by testing a set of candidate models that included additive uncorrelated covariates as main effects. The best supported model was selected using AICc [53].…”

Characterizing multispecies connectivity across a transfrontier conservation landscape

“…We combined model coefficients (non‐standardized) with 250‐m resolution grids of the landscape variables using a logit transformation to obtain probability surfaces with grid cell values ranging from 0 to 1 (Naidoo et al, 2018; Osipova et al, 2019). We then used the inverse of these grid cell values to generate landscape resistance surfaces (Zeller et al, 2012).…”

Conservation from the inside‐out: Winning space and a place for wildlife in working landscapes

“…In the case of the African savannas, wildlife survival, abundance and resilience to seasonal flux and drought are also scale‐dependent, and like livestock, they depend on the ecological benefits accruing across large functionally heterogeneous landscapes (Fryxell et al, ; Owen‐Smith, ; Western & Gichohi, ). Species such as elephants, lions, wild dogs, giraffe and migratory wildebeest, zebra and gazelle in the Kenya–Tanzania borderlands cover thousands of square kilometres in the course of seasonal movements (Dolrenry, Stenglein, Hazzah, Lutz, & Frank, ; Fryxell et al, ; Mose, Nguyen‐Huu, Western, Auger, & Nyandwi, ; Osipova et al, ). In that species richness, habitat diversity and ecosystem integrity all increase with landscape heterogeneity (Peterson, Allen, & Holling, ; Figure ), conserving metapopulations of landscape species—species using a large geographic area which includes a wide variety of other species—conserves biological diversity and integrity in the process.…”